Dirk Fasshauer

Transmembrane domains (TMDs) anchor proteins within membranes of distinct composition and biophysical properties, necessitating adaptation to each membrane's unique environment. SNARE proteins, the core mediators of eukaryotic membrane fusion, provide an ideal system to study such adaptations: they are ubiquitous across Eukaryota, with paralogs localized to different compartments that have evolved independently to match their membrane context. Here, we combine statistical analyses of approximately 14 000 SNARE TMDs with MD simulations of 28 human SNARE TMDs to uncover how TMDs have adapted to distinct membrane environments. We identify a clear compositional dichotomy that separates SNAREs of the early secretory pathway (ER and Golgi apparatus) from those of the late secretory and endosomal pathways: early TMDs are enriched in bulky Phe residues, whereas late TMDs are dominated by smaller Ile residues. The larger Phe side chains likely enhance hydrophobic interactions in loosely packed ER and Golgi membranes, while Ile likely prevents disruption of the tight lipid‐lipid packing in the plasma and endosomal membranes, potentially contributing to protein localization. TMD lengths derived from MD simulations differ from those inferred by sequence‐based approaches and show limited variation across compartments. Together, these results reveal how variations in membrane composition shaped SNARE TMDs across eukaryotic compartments.

Cyclin-dependent kinase 4 (CDK4) is best known for its canonical role in cell-cycle control, yet how CDK4 activity intersects with cellular architecture remains poorly defined. Here, we uncover a non-canonical function of CDK4 in maintaining cytoskeletal mechanical homeostasis in triple-negative breast cancer (TNBC) cells. We show that CDK4 phosphorylates the RhoA-targeting RhoGAP Myo9b at serine 1935, enhancing its GAP activity and restraining RhoA–ROCK–pMLC-dependent actomyosin contractility. Loss or inhibition of CDK4 alters cell morphology, disrupts actin organization, and increases contractility. Elevated contractility in CDK4-deficient cells induces collapse of the intermediate filament network, characterized by Vimentin reorganization and mitochondrial redistribution, indicating a higher-order defect in cytoskeletal architecture. Furthermore, CDK4 expression negatively correlates with pMLC levels in both mouse TNBC tumors and human breast cancer samples, supporting the physiological relevance of this pathway. Together, these findings identify CDK4 as a regulator of cellular mechanical stability, integrating actin dynamics, intermediate filament integrity, and organelle positioning, and reveal an unexpected role for CDK4 beyond cell-cycle regulation.

SNARE proteins are central to eukaryotic cell biology, where they drive membrane fusion by assembling into four-helix bundles that bring opposing membranes into close proximity. Their ubiquitous role in intracellular membrane trafficking raises fundamental questions about their evolutionary origin and the emergence of eukaryotic cellular complexity. Here, we characterize SNARE-like proteins from Heimdallarchaeota, a lineage within the Asgard archaea that is closely related to eukaryotes. We show that a Heimdall SNARE forms a stable homotetrameric four-helix bundle in solution and determine its structure by X-ray crystallography. Strikingly, the Heimdall complex closely resembles eukaryotic SNARE complexes in its overall architecture and core organization, despite being composed of four identical subunits. Molecular dynamics simulations further reveal conserved physical features of the bundle alongside distinctive properties of its central 0-layer. These findings demonstrate that the characteristic four-helix architecture of SNAREs predates the emergence of eukaryotic cells and provide structural insight into the evolution of the membrane fusion machinery.

Allosteric communication is fundamental to the function of proteins, but identifying the residue‐level pathways through which signals travel and their directionality is still a major challenge. Here we present a multi‐metric information‐theoretic framework that identifies candidate allosteric communication pathways from a single protein crystal structure in seconds. The method combines Transfer Entropy (TE) from the Gaussian Network Model to assign a model‐based directional asymmetry to residue‐residue coupling, Mutual Information (MI) to quantify coupling strength, and Conditional Mutual Information (CMI) to detect relay residues that mediate indirect couplings. At the network level, Burton–Pemantle ensemble random spanning trees provide robustness‐weighted betweenness centrality, differentiating persistent communication bottlenecks from occasional hubs. Kullback–Leibler (KL) divergence of the magnitude of the net transfer entropy distributions quantifies network rewiring and identifies allosteric switches. We validate the framework on four experimentally characterized systems: PDZ3 of PSD‐95, p38α MAP kinase, KRAS WT versus the oncogenic G12D mutant, and kinesin‐5 in ATP versus ADP bound states. Quantitative validation shows that the workflow captures previously reported hotspots and exceeds MI‐only and contact graph shortest‐path baselines on the all‐paths overlap metric, while performing at least as well as topology‐matched random controls. Computations take from ~14 s for a 110‐residue domain to ~7 min for a 350‐residue domain. on a standard laptop. Thus, the method can be applied systematically to large families of proteins.

Transmembrane domains (TMDs) anchor proteins within membranes of distinct composition and biophysical properties, necessitating adaptation to each membrane's unique environment. SNARE proteins, the core mediators of eukaryotic membrane fusion, provide an ideal system to study such adaptations: they are ubiquitous across Eukaryota, with paralogs localized to different compartments that have evolved independently to match their membrane context. Here, we combine statistical analyses of approximately 14,000 SNARE TMDs with MD simulations of 28 human SNARE TMDs to uncover how TMDs have adapted to distinct membrane environments. We identify a clear compositional dichotomy that separates SNAREs of the early secretory pathway (ER and Golgi apparatus) from those of the late secretory and endosomal pathways: early TMDs are enriched in bulky Phe residues, whereas late TMDs are dominated by smaller Ile residues. The larger Phe side chains likely enhance hydrophobic interactions in loosely packed ER and Golgi membranes, while Ile likely prevents disruption of the tight lipid-lipid packing in the plasma and endosomal membranes, thereby contributing to protein localization. TMD lengths derived from MD simulations differ from those inferred by sequence-based approaches and show limited variations across compartments. Together, these results reveal how variations in membrane composition shaped SNARE TMDs across eukaryotic compartments.

Protein sequence determines structure, function, and dynamics, yet the gap between sequenced proteins and experimentally determined structures continues to widen. While machine learning approaches like AlphaFold2 have transformed structural biology, they require substantial computational resources. Coevolution-based methods such as mutual information (MI) and direct coupling analysis (DCA), such as GREMLIN, offer alternatives but depend on extensive multiple sequence alignments with thousands of homologs. Here, we present a template-based pattern-matching approach that predicts protein contact maps by identifying conserved structural motifs from homologous experimental structures. Our method encodes spatial arrangements of up to five residues within 8.0 Å distance as sequence patterns, then aligns these patterns to query sequences to predict residue–residue contacts. Critically, our approach requires only a modest number of structural templates (typically 50–500) and runs on standard hardware without graphics processing units or high-performance computing clusters, processing proteins in 12–16 min regardless of length. We validated our method on 25 well-characterized protein domains, achieving correlations of 0.735–0.942 with experimental contact maps. Comparative analysis against MI and GREMLIN demonstrated that our method achieved better contact coverage while maintaining comparable accuracy. To demonstrate broader applicability, we tested on 7599 poorly annotated sequences using high-confidence AlphaFold structures as reference, achieving mean F 1-score of 0.609 ± 0.095 and accuracy of 0.954 ± 0.036. Our pattern matching approach provides a computationally efficient, interpretable alternative to both deep learning and coevolution-based methods, particularly valuable for proteins with limited sequence homologs or when rapid predictions are needed.

Soluble N‐ethylmaleimide‐sensitive factor Attachment protein REceptor (SNARE) proteins catalyze the fusion process of vesicles with target membranes in eukaryotic cells. To do this, they assemble in a zipper‐like fashion into stable complexes between the membranes. Structural studies have shown that the complexes consist of four different helices, which we subdivide into Qa‐, Qb‐, Qc‐, and R‐helix on the basis of their sequence signatures. Using a combination of biochemistry, modeling and molecular dynamics, we investigated how the four different types are arranged in a complex. We found that there is a matching pattern in the core of the complex that dictates the position of the four fundamental SNARE types in the bundle, resulting in a QabcR complex. In the cell, several different cognate QabcR‐SNARE complexes catalyze the different transport steps between the compartments of the endomembrane system. Each of these cognate QabcR complexes is compiled from a repertoire of about 20 SNARE subtypes. Our studies show that exchange within the four types is largely tolerated structurally, although some non‐cognate exchanges lead to structural imbalances. This suggests that SNARE complexes have evolved for a catalytic mechanism, a mechanism that leaves little scope for selectivity beyond the QabcR rule.

The amino acid sequence determines the structure, function, and dynamics of a protein. In recent years, enormous progress has been made in translating sequence information into 3D structural information using artificial intelligence. However, because of the underlying methodology, it is an immense computational challenge to extract this information from the ever-increasing number of sequences. In the present study, we show that it is possible to create 2D contact maps from sequences, for which only a few exemplary structures are available on a laptop without the need for GPUs. This is achieved by using a pattern-matching approach. The resulting contact maps largely reflect the interactions in the 3D structures and contain information about its function and dynamics. This approach was used to explore the evolutionarily conserved allosteric mechanisms and identify the source– sink (driver-driven) relationships by using an established method that combines Schreiber’s concept of entropy transfer with a simple Gaussian network model. The validity of our method was tested on the DHFR, PDZ, SH3, and S100 domains, with our predictions consistently aligning with the experimental findings.

Soluble N-ethylmaleimide-sensitive factor Attachment protein REceptor (SNARE) proteins catalyze the fusion process of vesicles with target membranes in eukaryotic cells. To do this, they assemble in a zipper-like fashion into stable complexes between the membranes. Structural studies have shown that the complexes consist of four different helices, which we subdivide into Qa-, Qb-, Qc-, and R-helix on the basis of their sequence signatures. Using a combination of biochemistry, modeling and molecular dynamics, we investigated how the four different types are arranged in a complex. We found that there is a matching pattern in the core of the complex that dictates the position of the four fundamental SNARE types in the bundle, resulting in a QabcR complex. In the cell, several different cognate QabcR-SNARE complexes catalyze the different transport steps between the compartments of the endomembrane system. Each of these cognate QabcR complexes is compiled from a repertoire of about 20 SNARE subtypes. Our studies show that exchange within the four types is largely tolerated structurally, although some non-cognate exchanges lead to structural imbalances. This suggests that SNARE complexes have evolved for a catalytic mechanism, a mechanism that leaves little scope for selectivity beyond the QabcR rule.

Neurotransmitters are released from synaptic vesicles, the membrane of which fuses with the plasma membrane upon calcium influx. This membrane fusion reaction is driven by the formation of a tight complex comprising the plasma membrane N‐ethylmaleimide‐sensitive factor attachment receptor (SNARE) proteins syntaxin‐1a and SNAP‐25 with the vesicle SNARE protein synaptobrevin. The neuronal protein Munc18‐1 forms a stable complex with syntaxin‐1a. Biochemically, syntaxin‐1a cannot escape the tight grip of Munc18‐1, so formation of the SNARE complex is inhibited. However, Munc18‐1 is essential for the release of neurotransmitters in vivo. It has therefore been assumed that Munc18‐1 makes the bound syntaxin‐1a available for SNARE complex formation. Exactly how this occurs is still unclear, but it is assumed that structural rearrangements occur. Here, we used a series of mutations to specifically weaken the complex at different positions in order to induce these rearrangements biochemically. Our approach was guided through sequence and structural analysis and supported by molecular dynamics simulations. Subsequently, we created a homology model showing the complex in an altered conformation. This conformation presumably represents a more open arrangement of syntaxin‐1a that permits the formation of a SNARE complex to be initiated while still bound to Munc18‐1. In the future, research should investigate how this central reaction for neuronal communication is controlled by other proteins.